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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nitrous oxide inhibition of methanogenesis represents an underappreciated greenhouse gas emission feedback

Methane (CH 4 ) and nitrous oxide (N 2 O) are major greenhouse gases that are predominantly generated by microbial activities in anoxic environments. N 2 O inhibition of methanogenesis has been reported, but comprehensive efforts to obtain kinetic information are lacking. Using the model methanogen Methanosarcina barkeri strain Fusaro and digester sludge-derived methanogenic enrichment cultures, we conducted growth yield and kinetic measurements and showed that micromolar concentrations of N 2 O suppress the growth of methanogens and CH 4 production from major methanogenic substrate classes. Acetoclastic methanogenesis, estimated to account for two-thirds of the annual 1 billion metric tons of biogenic CH 4 , was most sensitive to N 2 O, with inhibitory constants (K I ) in the range of 18–25 μM, followed by hydrogenotrophic (K I , 60–90 μM) and methylotrophic (K I , 110–130 μM) methanogenesis. Dissolved N 2 O concentrations exceeding these K I values are not uncommon in managed (i.e. fertilized soils and wastewater treatment plants) and unmanaged ecosystems. Future greenhouse gas emissions remain uncertain, particularly from critical zone environments (e.g. thawing permafrost) with large amounts of stored nitrogenous and carbonaceous materials that are experiencing unprecedented warming. Incorporating relevant feedback effects, such as the significant N 2 O inhibition on methanogenesis, can refine climate models and improve predictive capabilities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Global variations in critical drought thresholds that impact vegetation

ABSTRACT Identifying the thresholds of drought that, if crossed, suppress vegetation functioning is vital for accurate quantification of how land ecosystems respond to climate variability and change. We present a globally applicable framework to identify drought thresholds for vegetation responses to different levels of known soil-moisture deficits using four remotely sensed vegetation proxies spanning 2001–2018. The thresholds identified represent critical inflection points for changing vegetation responses from highly resistant to highly vulnerable in response to drought stress, and as a warning signal for substantial vegetation impacts. Drought thresholds varied geographically, with much lower percentiles of soil-moisture anomalies in vegetated areas covered by more forests, corresponding to a comparably stronger capacity to mitigate soil water deficit stress in forested ecosystems. Generally, those lower thresholds are detected in more humid climates. State-of-the-art land models, however, overestimated thresholds of soil moisture (i.e. overestimating drought impacts), especially in more humid areas with higher forest covers and arid areas with few forest covers. Based on climate model projections, we predict that the risk of vegetation damage will increase by the end of the twenty-first century in some hotspots like East Asia, Europe, Amazon, southern Australia and eastern and southern Africa. Our data-based results will inform projections on future drought impacts on terrestrial ecosystems and provide an effective tool for drought management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Microbial macroecology: In search of mechanisms governing microbial biogeographic patterns

Abstract Introduction Rapidly advancing technologies and accumulating information about microbial communities across the globe allow the quantification of microbial properties and functions at a macro‐scale. These emerging microbial biogeographic patterns call for a practical macroecological approach to investigate their underlying mechanisms. Aims The primary aims of this paper are to review the advancements of microbial macroecology in seeking mechanisms governing microbial biogeographic patterns, and to further lay out a roadmap for microbial macroecology in 10 years. Methods We reviewed the progress of microbial macroecology and demonstrated the application of the microbial macroecological approach to microbial biogeographic patterns with three case studies. Results Microbial macroecology provides a platform for understanding microbial abundance, community structure, and functioning across space, time, and taxonomic hierarchy. It emphasizes the integral effects of environmental filtering, microbial responses, diversification, dispersal, and local extinction that drive the microbial biogeographic patterns. The microbial macroecological approach emphasizes the last two stages of the four‐stage scientific method applied to microbial ecology: (a) describing microbial traits across scales to reveal patterns, (b) mathematically representing these patterns, (c) developing and testing conceptual models to build a mechanistic understanding of these patterns from a macroecological perspective, (d) plugging the new knowledge into the theoretical advancements. Three case studies were used to demonstrate the microbial macroecological approach for understanding the global patterns of microbial biomass carbon, microbial composition (fungi : bacteria ratio), and microbial carbon use efficiency. Conclusions Microbial macroecology offers a platform for understanding the mechanisms that drive biogeographic patterns of microbial abundance, diversity and functions. It is likely that these patterns and mechanisms will be increasingly incorporated into predictive models that link climate, carbon dynamics, and biogeochemical processes. A roadmap is outlined for the growing microbial macroecology field; we expect significant progress will be made in five research directions over the next 10 years.

Xu, Xiaofeng↗
DOE OSTI2023

Microbial Interactions Related to N 2 O Emissions and Temperature Sensitivity from Rice Paddy Fields

The soil microbiome is a driver of nitrous oxide (N 2 O) emissions in terrestrial ecosystems. Identifying the core microbiome of N 2 O emissions and its temperature sensitivity from trillions of soil microorganisms is a great challenge and is essential to improving the predictability of soil-climate feedback related to increasing temperature. Here, the integrated soil microbiome covering archaeal, bacterial, fungal, algal, and microfaunal communities was studied to disengage the potential linkage with its N 2 O emissions and its temperature sensitivity in paddy fields by hunting for core species pairs. The results showed that between-group interactions of core bacterial and archaeal members and the within-group interactions of core bacterial members jointly contributed to the N 2 O emissions and its temperature sensitivity. The contribution of between-group interactions (32 to 33%) was greater than that of within groups (10 to 18%). These results suggested that N 2 O emissions and their fluctuations related to climate warming are affected by the within- and between-group interactions of the soil microbiome. Our results help advance the knowledge on the importance of microbial keystone species and network associations in controlling N 2 O production and their responses to increasing temperature.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Artificial Intelligence for Accelerating Nuclear Applications, Science, and Technology

Artificial intelligence (AI) and machine learning (ML) methods have had significant impacts in science and technology in recent years. These methods for generating models from datasets or logic-based algorithms that emulate aspects of human performance can similarly accelerate the fields of nuclear applications, science, and technology toward the IAEA goals of contributing to peace, health, and prosperity. In order to accomplish advances with AI in general and ML in particular across these fields, IAEA can play a significant role by establishing, hosting and curating centralised resources, including databases, adhering to FAIR (findable, accessible, interoperable and reusable) principles and Open Science best practices, providing stewardship of data sharing, supporting training efforts and development of relevant workforces, as well as enabling connections among the scientific, technology, mathematics, AI and ethics communities. Many areas can benefit from the use of AI in the realm of nuclear applications. In human health, these areas include clinical research, epidemiology, nutrition, medical imaging, radiotherapy and education of health professionals. AI-based tools are also being used to facilitate different clinical tasks in imaging, computer-assisted diagnosis in mammography and lung cancer screening programmes, and dose prediction in nuclear medicine procedures. ML methods in particular may also increase the efficiency and accuracy of the analysis of computerised tomography and dual-energy absorptiometry scans for body composition and bone analysis. The application of AI methods to nuclear and related technologies in food and agriculture can lead to significant advances and improved efficiency in the optimisation of agricultural production, food product development, management of supply chains, food safety and food authenticity control. In the water and environmental sector, AI can help inform policies to mitigate the world’s water problems. The application of AI techniques to hydrology and environmental sciences is expected to improve patterns identification and enable model predictions under a changing climate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Tradeoffs and Synergies in Tropical Forest Root Traits and Dynamics for Nutrient and Water Acquisition: Field and Modeling Advances

Vegetation processes are fundamentally limited by nutrient and water availability, the uptake of which is mediated by plant roots in terrestrial ecosystems. While tropical forests play a central role in global water, carbon, and nutrient cycling, we know very little about tradeoffs and synergies in root traits that respond to resource scarcity. Tropical trees face a unique set of resource limitations, with rock-derived nutrients and moisture seasonality governing many ecosystem functions, and nutrient versus water availability often separated spatially and temporally. Root traits that characterize biomass, depth distributions, production and phenology, morphology, physiology, chemistry, and symbiotic relationships can be predictive of plants’ capacities to access and acquire nutrients and water, with links to aboveground processes like transpiration, wood productivity, and leaf phenology. In this review, we identify an emerging trend in the literature that tropical fine root biomass and production in surface soils are greatest in infertile or sufficiently moist soils. We also identify interesting paradoxes in tropical forest root responses to changing resources that merit further exploration. For example, specific root length, which typically increases under resource scarcity to expand the volume of soil explored, instead can increase with greater base cation availability, both across natural tropical forest gradients and in fertilization experiments. Also, nutrient additions, rather than reducing mycorrhizal colonization of fine roots as might be expected, increased colonization rates under scenarios of water scarcity in some forests. Efforts to include fine root traits and functions in vegetation models have grown more sophisticated over time, yet there is a disconnect between the emphasis in models characterizing nutrient and water uptake rates and carbon costs versus the emphasis in field experiments on measuring root biomass, production, and morphology in response to changes in resource availability. Closer integration of field and modeling efforts could connect mechanistic investigation of fine-root dynamics to ecosystem-scale understanding of nutrient and water cycling, allowing us to better predict tropical forest-climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Micro-spectroscopic and freezing characterization of ice-nucleating particles collected in the marine boundary layer in the eastern North Atlantic

Abstract. Formation of atmospheric ice plays a crucial role in the microphysical evolution of mixed-phase and cirrus clouds and thus climate. How aerosol particles impact ice crystal formation by acting as ice-nucleating particles (INPs) is a subject of intense research activities. To improve understanding of atmospheric INPs, we examined daytime and nighttime particles collected during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign conducted in summer 2017. Collected particles, representative of a remote marine environment, were investigated for their propensity to serve as INPs in the immersion freezing (IMF) and deposition ice nucleation (DIN) modes. The particle population was characterized by chemical imaging techniques such as computer-controlled scanning electron microscopy with energy-dispersive X-ray analysis (CCSEM/EDX) and scanning transmission X-ray microscopy with near-edge X-ray absorption fine-structure spectroscopy (STXM/NEXAFS). Four major particle-type classes were identified where internally mixed inorganic–organic particles make up the majority of the analyzed particles. Following ice nucleation experiments, individual INPs were identified and characterized by SEM/EDX. The identified INP types belong to the major particle-type classes consisting of fresh sea salt with organics or processed sea salt containing dust and sulfur with organics. Ice nucleation experiments show IMF events at temperatures as low as 231 K, including the subsaturated regime. DIN events were observed at lower temperatures of 210 to 231 K. IMF and DIN observations were analyzed with regard to activated INP fraction, ice-nucleation active site (INAS) densities, and a water activity-based immersion freezing model (ABIFM) yielding heterogeneous ice nucleation rate coefficients. Observed IMF and DIN events of ice formation and corresponding derived freezing rates demonstrate that the marine boundary layer aerosol particles can serve as INPs under typical mixed-phase and cirrus cloud conditions. The derived IMF and DIN parameterizations allow for implementation in cloud and climate models to evaluate predictive effects of atmospheric ice crystal formation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1983

Space station architectural concepts and functional capability

Space program goals that NASA can best achieve by the construction of a space station in keeping with the 1958 directive to maintain U.S. pre-eminence in space technology are discussed. Science goals that can be satisfied by a suitable equipped space station include a deeper understanding of the earth/sun system and the earth as a planet, the acquisition of new data on the evolution of the solar system, of life, and of the universe, and the extended study of the laws governing the state of matter and energy. Application goals that can be pursued with a space station include assaying all renewable and nonrenewable earth resources, predicting environment, weather, and climatic changes, studying ocean dynamics, using space to develop new processes and materials, and using space for information transmission on a global basis. The space station can serve as a waypoint for voyages by manned or unmanned spacecraft, as a laboratory, observation platform, and technology proving station, and as a base for deployment and repair of other spacecraft.

Herman, D. H.↗
NASA NTRS1993

GEWEX Cloud Systems Study (GCSS)

The Global Energy and Water Cycle Experiment (GEWEX) Cloud Systems Study (GCSS) program seeks to improve the physical understanding of sub-grid scale cloud processes and their representation in parameterization schemes. By improving the description and understanding of key cloud system processes, GCSS aims to develop the necessary parameterizations in climate and numerical weather prediction (NWP) models. GCSS will address these issues mainly through the development and use of cloud-resolving or cumulus ensemble models to generate realizations of a set of archetypal cloud systems. The focus of GCSS is on mesoscale cloud systems, including precipitating convectively-driven cloud systems like MCS's and boundary layer clouds, rather than individual clouds, and on their large-scale effects. Some of the key scientific issues confronting GCSS that particularly relate to research activities in the central U.S. are presented.

Moncrieff, Mitch↗
NASA NTRS1994

NASA atmospheric effects of aviation projects: Status and plans

NASA's Atmospheric Effects of Aviation Project is developing a scientific basis for assessment of the atmospheric impact of subsonic and supersonic aviation. Issues addressed include predicted ozone changes and climatic impact, and related uncertainties. A primary goal is to assist assessments of United Nations scientific organizations and, hence, consideration of emission standards by the International Civil Aviation Organization. Project focus is on simulation of atmospheric processes by computer models, but studies of aircraft operations, laboratory studies, and remote and in situ observations of chemical, dynamic, and radiative processes are also included.

Wesoky, Howard L.↗
NASA NTRS1999

Climatological Structures of the GRIPS Models: Mean States and Forcing

The GCM-Reality Intercomparison Project for SPARC (GRIPS) is assessing and monitoring the performance of state-of-the-art general circulation models (GCMs). A wide variety of tasks have been initiated. These are designed to: (1) assess the ability of the GCMs to represent the current climatological structure of the troposphere and middle atmosphere,(2) to compare their response to imposed forcing anomalies, and (3) to estimate the certainty with which future climate perturbations can be predicted. This paper is concerned with assessments of the climatological states in the GCM simulations. Comparing the simulations with observational datasets reveals considerable discrepancies in the modelled fields. While it might be anticipated that certain types of biases in the model simulations might be related to the formulation of different aspects of the numerical package (dynamical schemes, cloud schemes, radiation transfer, inclusion of gravity wave drag), there is no clear relationship between these features. This paper attempts to draw a more comprehensive picture of the GCMs'performance than has previously been shown, by comparing the dominant forcing mechanisms in the models with observational estimates, and relating model deficiencies to the differences in the physical mechanisms in the GCMS.

Pawson, Steven↗
NASA NTRS1999

Climate Change and a Global City: An Assessment of the Metropolitan East Coast Region

The objective of the research is to derive an assessment of the potential climate change impacts on a global city - in this case the 31 county region that comprises the New York City metropolitan area. This study comprises one of the regional components that contribute to the ongoing U.S. National Assessment: The Potential Consequences of Climate Variability and Change and is an application of state-of-the-art climate change science to a set of linked sectoral assessment analyses for the Metro East Coast (MEC) region. We illustrate how three interacting elements of global cities react and respond to climate variability and change with a broad conceptual model. These elements include: people (e.g., socio- demographic conditions), place (e.g., physical systems), and pulse (e.g., decision-making and economic activities). The model assumes that a comprehensive assessment of potential climate change can be derived from examining the impacts within each of these elements and at their intersections. Thus, the assessment attempts to determine the within-element and the inter-element effects. Five interacting sector studies representing the three intersecting elements are evaluated. They include the Coastal Zone, Infrastructure, Water Supply, Public Health, and Institutional Decision-making. Each study assesses potential climate change impacts on the sector and on the intersecting elements, through the analysis of the following parts: 1. Current conditions of sector in the region; 2. Lessons and evidence derived from past climate variability; 3. Scenario predictions affecting sector; potential impacts of scenario predictions; 4. Knowledge/information gaps and critical issues including identification of additional research questions, effectiveness of modeling efforts, equity of impacts, potential non-local interactions, and policy recommendations; and 5. Identification of coping strategies - i.e., resilience building, mitigation strategies, new technologies, education that affects decision-making, and better preparedness for contingencies.

Rosenzweig, Cynthia↗
NASA NTRS2000

TRMM Surface Backscatter Measurements - Temporal and Spatial Analysis: Inter-Comparison with NSCAT

Global rainfall is the primary redistributor of earth's energy by the process of latent heat release. This forms the main driving force for the tropical circulation, which in turn impacts the global circulation .through transient events-such as El Nino. Hence, more precise and long-term time series of the rainfall and its variability is crucial to the understanding and prediction of the global climate and climate change. The Precipitation Radar (PR) abroad the US/Japan Tropical Rainfall Measuring Mission (TRMM) is the first radar ever launched into space that measures detailed vertical profiles of rain intensity over the tropics. One of the challenges in estimating rainfall from spaceborne radars is the presence of attenuation at frequencies, such as 14 GHz of the TRMM PR and future planned systems at this and higher frequencies. A common approach in current rainfall retrieval algorithms is to employed the path integrated attenuation (PIA) as a constraint to the retrieval, and hence overcome errors in the radar calibration or in the assumed rainfall parameters. PIA can either be derived from a radiometer or from the surface reference technique, in which a clear air radar measurement is compared with the measurement in the raining area. The current TRMM 2A21 PIA data product makes use of both a temporal and spatial clear air database for comparison to rainy measurements. In this paper we present results from analysis of TRMM surface backscatter cross-section (sigmaO) measurements from Nov 97-Feb99, and a comparison with sigmaO measurements obtained by the NASA Scatterometer (NSCAT) between Sept96-June97. Measurements for a given month from both instruments are compiled on a 1 deg. (lat.) x 1 deg. (lon.) x 1 hr. grid. This enables TRMM--NSCAT comparison and the investigation of seasonal and diurnal trends in both data sets. From preliminary analysis of TRMM sigmaO's we have decided not to treat the ocean as a single homogeneous region but to select a number of ocean sub-regions and individually analyze their trends. Likewise, and in a similar approach to previous studies of Seasat over-land data, we have selected a number of over-land regions for study. From said sigmaO maps and regional trend analysis we investigate possible sources of trends and variability. In addition, we study the effects of TRMM PR sensitivity through the PR "possible rain" class. Given NSCAT's inability to flag rain contaminated measurements we are able to gauge the impact of rain contamination on NSCAT monthly sigmaO maps, using TRMM measurements. The research described in this paper was carried out by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration (NASA), U.S.A.

Im, Eastwood↗
NASA NTRS2000

Early Results from the MODIS Atmosphere Cloud Algorithms

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of five instruments aboard the Terra Earth Observing System platform launched in December 1999. With 36 spectral bands from the visible through the infrared, and spatial resolution from 250m to 1km, the instrument provides an unprecedented opportunity for global cloud studies. A comprehensive set of remote sensing algorithms for cloud masking and retrieval of cloud physical and optical properties have been developed by members of the MODIS atmosphere team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud top physical parameters (temperature, pressure, emissivity), cloud phase, cloud optical parameters (optical depth, effective particle radius, water path), visible cirrus reflectance, a contrail flag, and other derived parameters. All products are archived into two categories: pixel-level retrievals at a 1 km or 5 km spatial resolution at nadir (referred to as Level-2 products) and 1 degree global gridded statistics (Level-3 products). An overview of the MODIS atmosphere algorithms and products, their status, validation activities, and early level-2 and -3 results will be presented.

Platnick, S.↗
NASA NTRS2001

Cloud Modeling

Numerical cloud models have been developed and applied extensively to study cloud-scale and mesoscale processes during the past four decades. The distinctive aspect of these cloud models is their ability to treat explicitly (or resolve) cloud-scale dynamics. This requires the cloud models to be formulated from the non-hydrostatic equations of motion that explicitly include the vertical acceleration terms since the vertical and horizontal scales of convection are similar. Such models are also necessary in order to allow gravity waves, such as those triggered by clouds, to be resolved explicitly. In contrast, the hydrostatic approximation, usually applied in global or regional models, does allow the presence of gravity waves. In addition, the availability of exponentially increasing computer capabilities has resulted in time integrations increasing from hours to days, domain grids boxes (points) increasing from less than 2000 to more than 2,500,000 grid points with 500 to 1000 m resolution, and 3-D models becoming increasingly prevalent. The cloud resolving model is now at a stage where it can provide reasonably accurate statistical information of the sub-grid, cloud-resolving processes poorly parameterized in climate models and numerical prediction models.

Tao, Wei-Kuo↗
NASA NTRS2001

Human Health Effects of Ozone Depletion From Stratospheric Aircraft

This report presents EPA's initial response to NASA's request to advise on potential environmental policy issues associated with the future development of supersonic flight technologies. Consistent with the scope of the study to which NASA and EPA agreed, EPA has evaluated only the environmental concerns related to the stratospheric ozone impacts of a hypothetical HSCT fleet, although recent research indicates that a fleet of HSCT is predicted to contribute to climate warming as well. This report also briefly describes the international and domestic institutional frameworks established to address stratospheric ozone depletion, as well as those established to control pollution from aircraft engine exhaust emissions.

Wey, Chowen↗
NASA NTRS2003

NASA's Scientific Agenda for GPM Mission

The objectives of the Global Precipitation Measurement (GPM) Mission are to: 1) Understand the horizontal and vertical structure of rainfall, its macro- and micro-physical nature, and its associated latent heating, 2) Train and calibrate retrieval algorithms for constellation radiometers, 3) Provide sufficient global sampling to significantly reduce uncertainties in short-term rainfall accumulations, and 4) Extend scientific and societal applications. The GPM mission design consists of a core satellite, constellation satellties, precipitation validation sites for error characterization, and a precipitation processing center. This viewgraph presentation profiles the science goals of the mission, and its capability for producing climate data and weather predictions.

Smith, Eric A.↗